Sustainability in train structures: An approach for LCA of new material combinations

Kurzfassung

The future of rail transport and mobility is characterised by the requirements of passengers, manufacturers, operators as well as the political environment. The DLR project Rolling Stock (RoSto) develops innovative technologies for the design of next-generation railway vehicles to fulfil the diverse requirements of different stakeholders. While the focus is on user-oriented interiors, safety concepts, and improved aerodynamics, the use of resource-efficient and sustainable materials is an important aspect for the design of structures that should not be neglected. Although rail transportation is nowadays regarded as comparatively environmentally beneficial compared to alternatives such as automobiles and airplanes, their components are made almost exclusively from energy intensive and non-renewable, only partially recyclable, materials. Therefore, the design of new elements in the RoSto project is supported by Life Cycle Assessment (LCA) as an established method for calculating potential environmental impacts of products over their complete life cycle. This concept is exemplarily shown here for the design of a future rail vehicles generic roof structure, establishing eco-design principles supported by LCA already in the early development phase. Among the list of potential materials are different types of wood, metals, and fibre reinforced polymers (FRP). From LCA perspective, todays challenge lies in the scattered nature of the available Life Cycle Inventory (LCI) data for such materials. However, many material systems differ considerably in their raw materials and production pathways and therefore need to be modelled with a higher level of detail to enable a fair comparison. The initial focus is on the use of different polymer systems within the roof structure. For this purpose, the application of three different resins is tested on its potential environmental effects and the results are then compared with each other as part of a parameter study. Additionally, background data sets from two databases available in OpenLCA, Ecoinvent and cm.chemicals, are analysed within this study and checked for any deviations and their implications on comparability. With the help of a sensitivity analysisand using the Environmental Footprint 3.1 impact assessment method., the results are placed in a comprehensive context in order to make future recommendations for the procedure of further investigations. This study is modelled in OpenLCA 2.3.1.